clean.subj.group: A function to remove outlier subjects

In EricMenetre/NPL: An incomplete toolkit for the researcher in NeuroPsychoLinguistic

Description

This function examines the data and gives back which subjects are to be removed because of mean RT above or under a certain number of standard deviations

Usage

clean.subj.group(
  subj.var,
  RT.var,
  N.sd,
  data,
  groupping = FALSE,
  group.var = NULL
)

Arguments

subj.var	Subject variable. Use the raw name of the column e.g. subjects instead of data$subjects without "" either
RT.var	Variable containing the reaction times. Use the raw name of the column e.g. RT instead of data$RT without "" either
N.sd	Number of standard deviation above and under the mean where to put the rejection boundary.
data	Name of the dataframe containing the experimental data.
groupping	Specify TRUE if results need to be differentiated by group. Default is FALSE. If set to TRUE, specify the group.var argument.
group.var	Groupping variable for example age group. Use the raw name of the column e.g. group instead of data$group without "" either. The default is NULL, use it like this without groupping variable in your data. This argument is linked to the groupping one. if groupping = TRUE, specify the group.var argument.

EricMenetre/NPL documentation built on June 23, 2021, 2:10 p.m.